The term ‘uniques’ is often used in web analytics as an abbreviation for unique web visitors (i.e. how many unique people visited my site). The problem is that counting unique visitors is fraught with problems that are so fundamental, it renders the term ‘uniques’ meaningless.

Firstly, cookies get lost, blocked and deleted. Research has shown that after a period of four weeks, nearly one third of tracking cookies are missing, which means the visitor will be incorrectly considered a new unique visitor should they return to the same website (see Accuracy Whitepaper for further reading).

The longer the time period, the greater the chance of this happening, which makes comparing year-on-year data invalid for example. In addition, browsers make it very easy these days for cookies to be removed – see the new ‘incognito’ features of the latest Firefox, Chrome and Internet Explorer browsers.

However, the biggest issue for counting uniques faced by both on and off-site web analytics tools is how many devices people use to access the web. For example, consider the following scenario:

You and your spouse are considering your next holiday. Your spouse first checks out possible locations on your joint PC at home and saves a list of website links.

The next evening you use the same PC to review these links. Unable to decide that night, you email the list to your office and the next day you continue your holiday checks during your lunch hour at work and also review these again on your mobile while commuting home on the train.

Day three of your search resumes at your friend’s house where you seek a second opinion. Finally you go home and book online using your shared PC.

The above scenario is actually very common – particularly if the value of the purchase is significant, which implies a longer consideration period and the seeking of a second opinion (spouse, friends work colleagues).

Simply put, there is not a web analytics solution in the world that can accurately track this scenario, that is to tie the data together from multiple devices and where multiple people have been involved, nor is there likely to be in the near future.

Combining these limitations leads to large error bars when it comes to tracking uniques. In fact these errors are so large that the metric is actually meaningless and should be avoided in favour of more accurate ‘visit’ data.

Update (Apr-09): coincidentally Eric Peterson also posted a much longer blog article on the same issues in March – here’s the link: